Facial expression tracking during augmented and virtual reality sessions

ABSTRACT

An example method for estimating an emotion based upon a facial expression of a user can include: receiving one or more captured facial expressions from the user at a visual computing device; comparing the one or more captured facial expressions to one or more known facial expressions; and assigning an emotion to the plurality of captured facial expressions based upon the comparing.

BACKGROUND

Augmented reality is a technology that can superimpose a virtual imageover an actual scene. Virtual reality is a technology that can provide acomputer generated simulation of a scene. A user can view the computersimulation of the scene with a virtual reality device such as a virtualreality headset. Augmented reality devices and virtual reality devicescan be considered to be visual computing devices.

When a user views a scene with a visual computing device, the scene canbe viewed from a perspective of the user. A user of an augmented realitydevice can view the scene looking outward through the augmented realitydevice. A user of a virtual reality device can view images generated onthe virtual reality headset.

SUMMARY

In one aspect, an example method for estimating an emotion based upon afacial expression of a user can include: receiving one or more capturedfacial expressions from the user at a visual computing device; comparingthe one or more captured facial expressions to one or more known facialexpressions; and assigning an emotion to the plurality of capturedfacial expressions based upon the comparing.

In another aspect, an example visual computing device that can be wornby a user can include: a processing unit; system memory; a display uniton which one or more virtual images can be projected; and a plurality ofcameras, the plurality of cameras being oriented in an inwardly-facingdirection towards a face of the user.

In yet another aspect, an example method implemented on a visualcomputing device can include: displaying, by the visual computingdevice, a first image to a user; capturing a facial expression of theuser as a result of the user viewing the first image on the visualcomputing device, the facial expression comprising a reaction of theuser to the first image; identifying a user emotion associated with thefacial expression; determining when the user emotion is negative; andwhen the user emotion is negative, displaying a second image to theuser, the second image being a modification of the first image or a newimage.

The details of one or more techniques are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages of these techniques will be apparent from the description,drawings, and claims.

DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an example system that supports facial expression trackingduring augmented reality and virtual reality sessions.

FIG. 2 shows example augmented reality goggles.

FIG. 3 shows example virtual reality goggles.

FIG. 4 shows a method implemented on the server computer of FIG. 1 fortraining the server computer to identify and recognize facialexpressions of a user.

FIG. 5 shows a method implemented on the server computer of FIG. 1 foridentifying facial expressions during an operational phase.

FIG. 6 shows a method implemented on a visual computing device of FIG. 1for tracking facial expressions of a user.

FIG. 7 shows example physical components of the server computer of FIG.1.

DETAILED DESCRIPTION

The present disclosure is directed to systems and methods for capturingand tracking user facial expressions when using a visual computingdevice, such as an augmented reality (AR) or a virtual reality (VR)device. Using the systems and methods, the visual computing device canbe modified to include one or more cameras that face inward and whichcan capture facial expressions of a user of the visual computing device.The facial expressions can be used to ascertain an emotional state ofthe user when viewing a scene with the visual computing device.

Based on the emotional state of the user, different imagery can bedisplayed on the visual computing device to attempt to impact theemotional state of the user. For example, if the user is viewing a sceneinvolving a car and a negative emotional state is detected, an image ofa different car can be presented in an attempt to create a positiveemotional state for the user. As another example, if the user is viewinga financial statement or a financial health status and a negativeemotional state is detected, different future financial scenarios,including action steps that can be taken, can be presented to the userin an attempt to provide a preferable emotional state for the user.

Using the systems and methods, a user's emotional reaction to a seriesof images can be captured and saved to create a baseline of emotionalreactions for the user. An initial training period can be used to createthe baseline of emotional reactions. Each image presented to the userduring the training period can evoke one or more emotional states in theuser. The emotional states can be captured. In addition, the user can beasked a series questions to determine whether the user has an emotionalconnection to an image before the user is presented with the image. Forexample, the user can be asked questions relating to the user's attitudetoward dogs before the user is presented one or more image of dogs. Anemotional reaction from the user to each image can be compared to user'sattitude toward dogs to permit a better interpretation of the user'semotional reaction.

After the training period, the user can view images on the visualcomputing device and the facial cameras on the visual computing devicecan capture and track the user's facial expressions when using theimages. When the user's facial expressions change, variances of theuser's facial expressions can be noted.

The user's facial expressions can be sent to an electronic computingdevice, for example a server computer, for analysis. The server computercan compare baseline user facial expressions obtained during thetraining period with the user's facial expressions when viewing imagesafter the training period. When a match is made between a user facialexpression obtained during the training period with a user facialexpression for a viewed image after the training period, the servercomputer can designate an emotional state associated with the facialexpression during the training period as an emotional state of the userwhen viewing the viewed image after the training period.

When the server computer determines that the emotional state of the useris a negative emotional state, for example sadness, anger or anxiety,the server computer can send an indication of the negative emotion tothe visual computing device. The visual computing device can then selecta new image for display on the visual computing device. The new imagecan be based on the current emotional state of the user and the currentviewed image such that the new image may produce a positive emotionalreaction in the user. For example, if the user is viewing a car that theuser may consider expensive and borderline affordable, the user mayexperience emotions such as sadness, anxiety or anger. However, if thevisual computing device selects an image for a more affordable car,taking into consideration the characteristics the user is known to wantin a car, the visual computing device may detect positive emotions suchas happiness and excitement. In some implementations, images for displayon the visual computing device can be selected by the server computerand sent to the visual computing device.

In some implementations, instead of performing the analysis describedabove herein on an electronic computing device such as a servercomputer, the analysis can be performed on the visual computing device.For example, the visual computing device can capture and store thefacial expressions of the user during the training period. The visualcomputing device can also access reference facial expressions from adatabase. In addition, the visual computing device can compare userfacial expressions captured during an operational period with the facialexpressions of the user during the training period and the referencefacial expressions from the database to identify a current emotionalstate of the user. The visual computing device can also display an imageon the visual computing device that can produce a positive emotion bythe user.

In an example implementation using a VR device, a customer of afinancial institution who is interested in purchasing a home can view asimulated image of a street with virtual representations of homesdisplayed on either side of the street. The financial institution candisplay the virtual representation of the homes based on a financialprofile of the customer and a profile of the customer's currentpurchasing interests. The VR device can capture the customer's facialexpressions while viewing the homes and send the customer's facialexpressions to a server computer of the financial institution. Theserver computer can compare the customer's facial expressions withfacial expressions of the customer captured during a training period.The server computer can then correlate facial expressions with anemotional state of the customer and attempt to determine the emotionalstate of the customer when viewing the homes. The VR device can alsodisplay a three-dimensional representation of the customer's currentspending.

Based on the emotional state of the customer, as the customer views thehomes and the customer's current spending, a determination can be madeas to what types of homes the customer prefers. For example, when theemotional state of the customer is happy when viewing smaller homes butunhappy when viewing larger homes (because the larger homes are notaffordable), the simulated image of the street can be replaced with asimulated image of another street which contains more small homes.

In this example, the customer can also change a geographical area of thehomes, for example to a different city. For example, the VR device canprovide a new simulated image showing virtual representations of homeson a street in a smaller city. However, in this example, the customer isnot pleased with the smaller homes because the smaller homes are not asnice as in the previous city. The customer can then make facialexpressions that can connote a negative emotional state. When thecustomer revises his budget allocations so that the customer can afforda better home, the VR device can display visual representations of nicersmall homes for display. When the customer makes facial expressions thatindicate that the customer is satisfied with the nicer smaller homes, aprofile for the customer can be updated, indicating the customer likesnicer small homes of a certain price range. The updated customer profilecan be used to provide better simulated images to the customer in thefuture.

The systems and methods disclosed herein are directed to a computertechnology that can improve a customer experience when using a visualcomputing device, such as an AR device or a VR device. The systems andmethods can permit a software application at a server computer to betrained to identify customer facial expressions when viewing images onthe visual computing device and to assign an emotion to each facialexpression. The system and methods can then permit the softwareapplication to identify emotional responses of the customer when viewingimages and permit new images to be presented to the user to create apositive emotional response for the customer. By quickly learning howthe user responds to different images, an organization can moreefficiently respond to the customer's needs by presenting offers to thecustomer that the customer is more likely to accept.

FIG. 1 shows an example system 100 that can support facial expressiontracking during augmented reality and virtual reality sessions. Theexample system 100 includes an augmented reality (AR) device 102, avirtual reality (VR) device 106, a network 110, a server computer 112and a database 116. The AR device 102 includes a reality managementmodule 104, the VR device 106 includes a reality management module 108and the server computer 112 includes a reaction management module 114.More, fewer or different modules are possible.

The example AR device 102 is an electronic computing device with an ARfunctionality that can be worn or carried by the user. An example of anAR device that may be worn by the user is an AR headset. An example ofan AR device that may be carried by the user is a smart telephone ortablet computer that includes AR components such as a processor, displayand camera and an AR software application.

The AR headset includes a wearable computer, a camera and an opticaldisplay. The wearable computer includes a wireless telecommunicationcapability, permitting a wireless connection between the wearablecomputer and one or more server computers. The wearable computer alsoincludes voice recognition capability, permitting the user to direct thewearable computer via voice commands. The optical display projectsvirtual images and also permits the user to see through the display. Anexample of an AR headset is Google Glass, from Google Inc. of MountainView, Calif.

The example VR device 106 is an electronic computing device thatsupports virtual reality. Virtual reality is a computer technology thatuses images, sounds and other sensations to replicate a real environmentor an imaginary setting, and simulates a user's physical presence inthis environment to enable the user to interact with the replicatedenvironment. The VR device 106 can comprise a head-mounted display, suchas goggles with an eye-viewable screen, that can provide a view of thereplicated environment and that can permit interaction with thereplicated environment. An example VR device is Oculus Rift, from OculusVR, LLC of Irvine, Calif.

The example network 110 is a computer network such as the Internet. Auser of AR device 102 or VR device 106 can login to server computer 112across network 110.

The server computer 112 is a server computer of a business organizationsuch as a financial institution, a retail organization or anotherorganization that can provide products or services to a customer of theorganization. Server computer 112 can interface with users at AR device102 and VR device 108 via network 110. More than one server computer canbe used.

Database 116 is an electronic database that can store financial andother profiles of the customer including a profile of user interests.Database 116 can also store virtual images that can be displayed on ARdevice 102 and VR device 106. In addition, database 116 can store dataregarding facial expressions and emotional reactions of the userobtained during and after the training period. Database 116 can beaccessed via server computer 112.

The example reality management module 104 and reality management module108 manage display presentations on AR device 102 and VR device 106,respectively to provide appropriate virtual image displays to the user.The virtual image displays can be obtained from server computer 112based on a current location of the user, a profile of user interests, afinancial health status of the user and an identified emotional state ofthe user. The reality management module 104 and reality managementmodule 108 determine where to place a virtual image display in a currentview of the user on AR device 102 or VR device 106.

The example reaction management module 114 receives user facialexpression data both during the training period for the user and duringan operational period. The reaction management module 114 creates abaseline of the user's emotional expressions during the training periodand compares the user's facial expressions during the operational periodwith the user's emotional expressions during the training period. As aresult of the comparison, the reaction management module 114 candetermine user emotional reactions during the operational period. Thereaction management module 114 can communicate the emotional reactionsto reality management module 104 or reality management module 108.

The reaction management module 114 can also personalize the baseline ofthe user's emotional expressions based on the user's particular reactionto an image, based on the responses of the user to the series ofquestions that can be asked the user about the image to attempt to gaugean emotional connection of the image to the user and based on learnedpatterns of the user's facial expressions over time. The reactionmanagement module 114 can personalize the baseline of the user'semotional expressions because the user's facial expressions may beunclear. The same facial expression from different users may connotedifferent emotions. For example, a facial expression that the reactionmanagement module 114 can interpret as a “sour face” may representsadness for one person but may represent joy for another person. Inaddition, one person may have more extreme emotions, whereas anotherperson may have more moderate emotions with more or less subtlevariation. Furthermore, establishing learned patterns or a chronology ofemotions over time can further determine which next images to show tothe user.

In some implementations, the reaction management module 114 can alsosend one or more virtual images to reality management module 104 orreality management module 108. In other implementations, the realitymanagement module 104 or reality management module 108 can obtain theone or more virtual images from virtual images that are stored on ARdevice 102 or VR device 106 or that have been previously downloaded toAR device 102 or VR device 106. In some implementations, thefunctionality of the reaction management module 114 described aboveherein can also be performed on AR device 102 or VR device 106.

FIG. 2 shows an example AR device 102 that comprises AR goggles. The ARdevice 102 includes four example inwardly-facing cameras 202, 204, 206and 208. The four inwardly-facing cameras 202, 204, 206, 208 can belocated at corners of the AR device 102, within a field of view of auser of AR device 102 and be oriented in an inward direction to the userof AR device 102. The inwardly-facing cameras 202, 204, 206 and 208 cancapture facial expressions of the user as the user views virtual imageson AR device 102. AR device 102 can send the captured facial expressionsto server computer 112.

FIG. 3 shows an example VR device 106 that comprises VR goggles. The VRdevice 106 includes a lens and display 302 for one eye and a lens anddisplay 304 for another eye. Each lens and display 302, 304 can focus apicture for each eye and create a stereoscopic 3D image. The VR device106 also includes four example inwardly-facing cameras 306, 308, 310 and314. The four inwardly-facing cameras are located within a field of viewof a user of VR device 106 and are oriented in an inward direction tothe user of VR device 106. A VR image can be displayed on VR device 106using lens and display 302 and lens and display 304. The inwardly-facingcameras 306, 308, 310 and 314 can capture facial expressions of the useras the user view virtual images on VR device 106. VR device 106 can sendthe captured facial expressions to server computer 112.

FIG. 4 shows a flowchart of an example method 400 for training a servercomputer to identify and recognize facial expressions of a user when theuser views virtual images on a visual computing device. For the examplemethod 400, the server computer is server computer 112.

At operation 402, questions are sent to an electronic computing deviceof the user, such as a smart phone, tablet computer, laptop computer ordesktop computer. The questions relate to topics or items that caninvoke different emotional states in the user. The questions are sent tothe user before the user views virtual images corresponding the topicsor items. The intent of the questions is to attempt to identify anemotional connection the user may have with the topic or item.

For example, one or more questions can elicit the user's opinion of petssuch as dogs and cats. Other questions can elicit the user's opinionsregarding vehicles, such as what vehicles the user would enjoy owningand what price range the user would want to pay for the vehicles. Stillother questions can be directed to a style of house the user prefers,what price range the user would be interested in paying for a house,what geographical area the user prefers to live it and what specificpart of the geographical area the user prefers—for example city orsuburb. The questions may be directed to what may be known about theuser, for example from an analysis of the user's interests, employmenthistory and status, and current financial health, assuming thisinformation is available. Other questions are possible.

At operation 404, server computer 112 receives user responses to thequestions.

At operation 406, one or more images are sent to the visual computingdevice for display on a display screen of the visual computing device.

At operation 408, facial expressions of the user are received from thevisual computing device. The facial expressions of the user are capturedat the visual computing device in response to the user viewing the oneor more images. The facial expressions are captured using theinwardly-facing cameras on the visual computing device.

At operation 410, a specific emotion for each facial expression isidentified. In one implementation, the specific emotion is identified bycomparing each facial expression with reference facial expressions thatcorrespond to specific emotions. For example, one reference facialexpression can show anger, another reference facial expression can showhappiness, another reference facial expression can show anxiety. Thereference facial expressions can be reference facial expressionscorresponding to specific emotions or a composite facial expression, forexample created from two or more facial expressions from operation 408that show a specific emotion. In addition, the reference facialexpression can be personalized for specific users corresponding to abaseline for the specific user. As discussed earlier herein, differentusers can have different emotional reactions to the same facialexpression.

Software on server computer 112 can analyze aspects of each facialexpression received at operation 408 with corresponding aspects of thereference facial expressions to make a determination the facialexpression received at operation 408 corresponds to the specific emotionof one of the reference facial expressions. Example aspects that can becompared can include a shape of the lips, characteristics of the eyesand a tension and position of facial muscles. Other or different aspectscan be compared. The analysis of the facial expressions can also takeinto consideration established emotional patterns of a user that can belearned over time. When a positive comparison is made, the specificemotion associated with the reference facial expression can be assignedto the facial expression received at operation 408.

At operation 412, a tag is assigned to each facial expression receivedat operation 408. The tag identifies the facial expression with thespecific emotion identified at operation 410.

FIG. 5 shows a flowchart of an example method 500 for identifying userfacial expressions during an operational phase. During the operationalphase, user facial expressions are captured when the user views one ormore images on the visual computing device. An attempt is then made toidentify a user emotion associated with each facial expression.

At operation 502, a facial expression is received from the visualcomputing device. The facial expression corresponds to a reaction of theuser when viewing an image on the visual computing device during theoperational phase. The facial expression is captured by theinwardly-facing cameras on the visual computing device in response tothe image viewed by the user on the visual computing device.

At operation 504, a specific emotion associated with the facialexpression received at operation 502 is identified. The specific emotionis identified by comparing the facial expression received at operation502 with a facial expression received during the training period or witha reference facial expression. For example, the facial expressionreceived at operation 502 can be compared with either a facialexpression received at operation 408 or a reference facial expressionfrom operation 410.

At operation 506, a message is sent to the visual computing device witha tag that identifies the specific emotion associated with the facialexpression received at operation 502.

At operation 508, a determination is made as to whether a negativeemotional state is detected. A negative emotional state can compriseemotions such as anger, sadness, frustration, anxiety and other similarnegative emotions.

At operation 508, when a negative emotional state is detected, atoperation 510 the set of images currently displayed on the visualcomputing device can be modified or replaced to create a new set ofimages. The intent of the new set of images is to inspire a positiveemotional reaction from the user. For example, if the user is viewing animage of a street scene and is reacting negatively to the homes on thestreet scene, the new set of images can comprise a different streetscene with a different set of homes. For example the new street scenecan include more or less expensive homes, depending on the user profileand the type of emotional reaction of the user to the current streetscene.

At operation 512, the new set of images is sent to the visual computingdevice.

At operation 514, a new set of facial expressions from the user isreceived based on the user emotional reaction to the new set of images.Control then returns to operation 508 and a determination is made as towhether a negative emotional state is detected based on an analysis ofthe user facial expressions from viewing the new set of images. Theprocess of operations 510-514 is then repeated as needed.

At operation 508, when a determination is made that a positive emotionalstate is detected, method 500 ends.

FIG. 6 shows a flowchart of an example method 600 for tracking facialexpressions of a user on a visual computing device. Based on an analysisof the facial expressions, a virtual image can be displayed on thevisual computing device that can result in a positive emotional reactionfrom the user. For example method 600, the visual computing device canbe an augmented reality electronics device, such as AR device 102 or avirtual reality electronics device, such as VR device 106.

At operation 602, one or more questions are received by the user fromserver computer 112 to determine an emotional connection of the user tocertain images. The questions are part of a training period to attemptto identify an emotional reaction of the user when viewing certainimages on the visual computing device. The questions can be received atan electronic computing device of the user, such as a smart phone, atablet computer, a laptop computer or a desktop computer. In someimplementations, the user can be asked to access a website associatedwith server computer 112 and answer the questions online.

The questions relate to a set of images that can invoke differentemotional states in the user. For example, one or more questions can askthe user's opinion of pets such as dogs and cats. Other questions canask the user's opinions regarding vehicles, such as what vehicles theuser would enjoy owning and what price range the user would want to payfor the vehicles. Still other questions can be directed to a style ofhouse the user prefers, what price range the user would be interested inpaying for a house, what geographical area the user prefers to live itand what specific part of the geographical area the user prefers—forexample city or suburb. The questions may be directed to what may beknown about the user, for example from an analysis of the user'sinterests, employment history and status, and current financial health,assuming this information is available. Other questions are possible.

At operation 604, the user sends responses to the questions to servercomputer 112. When the questions are sent to the user on an electroniccomputing device of the user, the user can send to the responses to theuser via the electronic computing device, for example the user's smartphone. When the user responds to the questions via a website, the usersimply submits answers to the questions via the website.

At operation 606, first images for the user are received at the visualcomputing device. The first images are received as part of the trainingperiod for server computer 112. The first images can correspond totopics corresponding to questions asked the user at operation 604.

At operation 608, the visual computing device captures facialexpressions of the user as the user views the first image on the visualcomputing device. Inwardly-facing cameras on the visual computing devicecan capture the facial expressions of the user.

At operation 610, the facial expressions of the user are sent to servercomputer 112. Server computer 112 attempts to identify an emotionalstate associated with the facial expression of the user, using theactual facial expression and information from the answered questions.

At operation 612, during an operational period following the trainingperiod, an additional facial expression is received at the visualcomputing device. The additional facial expression corresponds to anemotional reaction of the user to an image displayed on the visualcomputing device during the operational period.

At operation 614, a message is received from server computer 112 thatincludes a tag that identifies a specific emotion associated with theadditional facial expression.

At operation 616, a determination is made as to whether the specificemotion is a negative emotion, such as anger, frustration, anxiety orunhappiness.

At operation 616, when a determination is made that the specific emotionis a negative emotion, at operation 618, an image is identified at thevisual computing device that may result in a positive emotion from theuser.

At operation 620, the identified image is displayed on the visualcomputing device. Operations 612-620 can be repeated, if necessary, todetermine whether the user's emotional response to the identified imageis positive, and when the user's emotional response is not positive todisplay one or more additional images until a positive emotionalresponse is obtained from the user. At operation 616, when a positiveemotional state is detected, method 600 ends.

As illustrated in the example of FIG. 7, server computer 112 includes atleast one central processing unit (“CPU”) 702, a system memory 708, anda system bus 722 that couples the system memory 708 to the CPU 702. Thesystem memory 708 includes a random access memory (“RAM”) 710 and aread-only memory (“ROM”) 712. A basic input/output system that containsthe basic routines that help to transfer information between elementswithin the server computer 112, such as during startup, is stored in theROM 712. The server computer 112 further includes a mass storage device714. The mass storage device 714 is able to store software instructionsand data. Some or all of the components of the server computer 112 canalso be included in AR device 102 and VR device 106.

The mass storage device 714 is connected to the CPU 702 through a massstorage controller (not shown) connected to the system bus 722. The massstorage device 714 and its associated computer-readable data storagemedia provide non-volatile, non-transitory storage for the servercomputer 112. Although the description of computer-readable data storagemedia contained herein refers to a mass storage device, such as a harddisk or solid state disk, it should be appreciated by those skilled inthe art that computer-readable data storage media can be any availablenon-transitory, physical device or article of manufacture from which thecentral display station can read data and/or instructions.

Computer-readable data storage media include volatile and non-volatile,removable and non-removable media implemented in any method ortechnology for storage of information such as computer-readable softwareinstructions, data structures, program modules or other data. Exampletypes of computer-readable data storage media include, but are notlimited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid statememory technology, CD-ROMs, digital versatile discs (“DVDs”), otheroptical storage media, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe server computer 112.

According to various embodiments of the invention, the server computer112 may operate in a networked environment using logical connections toremote network devices through the network 720, such as a wirelessnetwork, the Internet, or another type of network. The server computer112 may connect to the network 720 through a network interface unit 704connected to the system bus 722. It should be appreciated that thenetwork interface unit 704 may also be utilized to connect to othertypes of networks and remote computing systems. The server computer 112also includes an input/output controller 706 for receiving andprocessing input from a number of other devices, including a touch userinterface display screen, or another type of input device. Similarly,the input/output controller 706 may provide output to a touch userinterface display screen or other type of output device.

As mentioned briefly above, the mass storage device 714 and the RAM 710of the server computer 112 can store software instructions and data. Thesoftware instructions include an operating system 718 suitable forcontrolling the operation of the server computer 112. The mass storagedevice 714 and/or the RAM 710 also store software instructions, thatwhen executed by the CPU 702, cause the server computer 112 to providethe functionality of the server computer 112 discussed in this document.For example, the mass storage device 714 and/or the RAM 710 can storesoftware instructions that, when executed by the CPU 702, cause theserver computer 112 to display received data on the display screen ofthe server computer 112.

Although various embodiments are described herein, those of ordinaryskill in the art will understand that many modifications may be madethereto within the scope of the present disclosure. Accordingly, it isnot intended that the scope of the disclosure in any way be limited bythe examples provided.

What is claimed is:
 1. A visual computing device that can be worn by auser, the visual computing device comprising: a processing unit; systemmemory; and a camera oriented towards a face of the user to capturefacial reactions of the user; wherein the system memory encodesinstructions that, when executed by the processing unit, cause thevisual computing device to: display a first image to the user, whereinthe first image depicts a first item associated with a financial profileof the user's current purchasing interests; capture, by the camera, afacial expression of the user as a result of the user viewing the firstimage, the facial expression comprising a reaction of the user to thefirst image; identify an emotion of the user corresponding to the facialexpression; determine when the captured facial expression is a negativeemotion; and when the emotion corresponding to the captured facialexpression is the negative emotion, display a second image to the userbased on the user's financial profile, wherein the second image depictsa second item that is (i) similar to the first item, and (ii) moreclosely-aligned to the user's financial profile based upon a cost of thesecond item.
 2. The visual computing device of claim 1, wherein thecamera is located within a field of view of the user.
 3. The visualcomputing device of claim 1, wherein the visual computing device is avirtual reality device.
 4. The visual computing device of claim 1,wherein the visual computing device is an augmented reality device. 5.The visual computing device of claim 4, wherein the augmented realitydevice further includes one or more outwardly-facing cameras which areoriented away from the face of the user.
 6. The visual computing deviceof claim 1, wherein the first image is an image of an automobile, andthe second image is an image of a more or less expensive automobile. 7.The visual computing device of claim 1, wherein the first image is animage of a first property and the second image is an image of a secondproperty for sale, wherein the first property and second property aredifferent in at least one of: price, style, location, and size.
 8. Amethod implemented on a virtual reality device, the method comprising:displaying, by the virtual reality device, a first image to a user,wherein the first image depicts a first item associated with a financialprofile of the user's current purchasing interests; orienting one ormore inwardly-facing cameras of the virtual reality device towards aface of the user; capturing a facial expression of the user, using theone or more inwardly-facing cameras, as a result of the user viewing thefirst image on the virtual reality device, the facial expressioncomprising a reaction of the user to the first image; sending thecaptured facial expression to an electronic computing device; receiving,from the electronic computing device, a message identifying a useremotion associated with the facial expression, the user emotionassociated with the facial expression being identified via a comparisonof the captured facial expression with a previous facial expression ofthe user obtained during a training period; determining whether the useremotion is negative; and when the user emotion is negative, displaying asecond image to the user based on the user's financial profile, whereinthe second image depicts a second item that is (i) similar to the firstitem, and (ii) more closely-aligned to the user's financial profilebased upon a cost of the second item.
 9. The method of claim 8, furthercomprising selecting the second image to produce a positive emotion bythe user.
 10. The method of claim 8, wherein the visual computing deviceis an augmented reality device or a virtual reality device.
 11. Themethod of claim 8, further comprising: displaying one or more possibleactions to be taken by the user to improve the financial health statusof the user; and capturing a second facial expression relating to theone or more possible actions.
 12. The method of claim 11, furthercomprising determining the user emotion associated with the one or morepossible actions based upon the second facial expression.
 13. The methodof claim 8, wherein the first image is an automobile, and the secondimage is a more or less expensive automobile.
 14. The method of claim 8,wherein the first image is an image of a first property and the secondimage is an image of a second property, wherein the first property forsale and second property are different in at least one of: price, style,location, and size.
 15. A visual computing device that can be worn by auser, the visual computing device comprising: a processing unit; systemmemory; and a camera oriented towards a face of the user to capturefacial reactions of the user; wherein the system memory encodesinstructions that, when executed by the processing unit, cause thevisual computing device to: present one or more questions associatedwith a plurality of topics to the user, the one or more questionsdirected at identifying an emotional connection of the user to theplurality of topics; receive one or more responses from the user to theone or more questions; based on the one or more responses, identify theemotion connection of the user to each of the plurality of topics;display a first image, wherein the first image depicts a first itemcorresponding to one of the plurality of topics to the user and aprofile of the user's current purchasing interests; capture, by thecamera, a facial expression of the user as a result of the user viewingthe first image, the facial expression comprising a reaction of the userto the image; identify an emotion of the user based on the capturedfacial expression and the one or more responses associated to the one ormore questions associated with the topic corresponding to the firstimage; determine when the captured facial expression is a negativeemotion; and when the emotion corresponding to the captured facialexpression is determined to be negative, display a second image to theuser based on the user's financial profile, wherein the second imagedepicts a second item that is (i) similar to the first item, and (ii)more closely-aligned to the user's financial profile based upon a costof the second item.
 16. The visual computing device of claim 15, whereinthe second image is selected, based on the one or more responses to theone or more questions associated with a plurality of topics, to resultin a positive emotion from the user.
 17. The visual computing device ofclaim 15, wherein the visual computing device is an augmented realitydevice.
 18. The visual computing device of claim 17, wherein theaugmented reality device further includes one or more outwardly-facingcameras which are oriented away from the face of the user.
 19. Thevisual computing device of claim 15, wherein the first image is an imageof an automobile, and the second image is an image of a more or lessexpensive automobile.
 20. The visual computing device of claim 15,wherein the first image is an image of a first property and the secondimage is an image of a second property, wherein the first property andsecond property are different in at least one of: price, style,location, and size.